{"title":"A vibratory-based method for road damage classification","authors":"F. Gunawan, Yanfi, B. Soewito","doi":"10.1109/ISITIA.2015.7219943","DOIUrl":null,"url":null,"abstract":"Automatic system to monitor the road condition is importance to minimize losses due to traffic accidents. The system is required considering the size of the road network in many modern metropolitan cities. Various monitoring techniques have been proposed and in this work, we evaluate the use of vehicle acceleration data in the longitudinal and lateral directions to detect the road anomalies particularly pothole. This article reports the characteristics of the data obtained from various road anomalies and identifies the statistical variance of the data with regard to the road anomalies.","PeriodicalId":124449,"journal":{"name":"2015 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Seminar on Intelligent Technology and Its Applications (ISITIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISITIA.2015.7219943","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17
Abstract
Automatic system to monitor the road condition is importance to minimize losses due to traffic accidents. The system is required considering the size of the road network in many modern metropolitan cities. Various monitoring techniques have been proposed and in this work, we evaluate the use of vehicle acceleration data in the longitudinal and lateral directions to detect the road anomalies particularly pothole. This article reports the characteristics of the data obtained from various road anomalies and identifies the statistical variance of the data with regard to the road anomalies.